FIG. 1 shows functional signal processing blocks in a typical cochlear implant system where K-Channel Filter Bank 101 pre-processes an initial acoustic audio signal x[n], for example, applying automatic gain control, noise reduction, etc. Each band pass filter in the K-Channel Filter Bank 101 is associated with a specific band of audio frequencies so that the acoustic audio signal x[n] is filtered into some K band pass signals, x1[n] to xK[n] where each signal corresponds to the band of frequencies for one of the band pass filters. For example, the initial acoustic audio signal x[n] may be spectrally decomposed into 12 time-domain band pass signals.
The band pass signals, x1[n] to xK[n] then are input to a Channel Processor 102 that extracts component signals that reflect specific stimulation information—e.g., a carrier signal containing fine time structure information and a modulator envelope signal. For example, in one specific system, the modulator envelope signal may be calculated using the Hilbert-Transform (incoherent decomposition). Based on these band pass signal signals, the Channel Processor 102 creates for each band pass channel a sequence of envelope weighted stimulation event signals p1[n] to pK[n], which represent specific requested stimulation events. For example, a sequence of envelope weighted stimulation event signals p1[n] to pK[n] may be based on channel specific sampling sequences (CSSS) as described in U.S. Pat. No. 6,594,525, which is incorporated herein by reference.
Pulse Weighting Module 103 further weights each requested envelope weighted stimulation event signal p1[n] to pK[n] based on a weighted matrix of stimulation amplitudes that reflect patient-specific perceptual characteristics to produce a set of channel stimulation signals q1[n] to qL[n] that provide an optimal tonotopic electrical representation of the acoustic signal. Equation 1 shows a typical weighting matrix of size M×N:
                    W        =                  (                                                    1                                            0.923                                            0.846                                            …                                            …                                            0                                            0                                            0                                                                    0                                            0.077                                            0.154                                            …                                            …                                            0                                            0                                            0                                                                    0                                            0                                            0                                            …                                            …                                            0                                            0                                            0                                                                    …                                            …                                            …                                            …                                            …                                            …                                            …                                            …                                                                    0                                            0                                            0                                            …                                            …                                            0.154                                            0.077                                            0                                                                    0                                            0                                            0                                            …                                            …                                            0.846                                            0.923                                            1                                              )                                    Equation        ⁢                                  ⁢        1            Matrix weighting of the stimulation pulses is described further in U.S. patent application 61/046,832, filed Apr. 22, 2008, which is incorporated herein by reference. In some embodiments, the number of filter bank channels may be greater than the number of electrode channels (e.g., 128:12). In such an arrangement, the stimulation event signals may be pooled into a smaller number of overlapping macro bands, and within each macro band the channel with the highest envelope is selected for a given sampling interval, as described for example in U.S. patent application 61/145,805, filed Jan. 20, 2009, which is incorporated herein by reference.
Finally, patient-specific fit of the stimulation signals can be further optimized by individual amplitude mapping and pulse shape definition in Pulse Shaper 104 which develops the set of electrode stimulation signals q1[n] to qL[n] into a set of output electrode pulses e1[n] to eL[n] to the stimulation electrodes in the implanted electrode array to stimulate the adjacent target nerve tissue. For example, this may involve maplaw, scaling, and/or pulse shaping functions.
The most apical region of the cochlea is associated with low-frequency perception. In this region, the corresponding electrode stimulation patterns in existing cochlear implant systems typically use both the fine time structure information of the carrier signal and the modulator envelope signal of the band pass signals to determine the electrode stimulation pattern. The modulator envelope signal defines the stimulation intensity (current, charge), and the fine time structure information determines the time instant when the stimulation occurs. The additional fine time structure information in the carrier signal may be used by the nervous structures in the inner ear, for example, to track changes in fundamental frequency (F0). This may be useful for better speech understanding, better perception of tonal languages and prosodic features, and better perception of music. For example, Channel Specific Sampling Sequences (CSSS) may be generated whenever a zero-crossing of the band pass carrier signal is detected, and the CSSS are weighted by the modulator envelope signal so as to provide both modulator information and fine time structure information. Envelope sampling is not performed on a regular time-grid, but rather is irregular and synchronous to the carrier signal.
The middle and basal regions of the cochlea are associated with the perception of mid- to high frequency audio. In these regions, the modulator envelope signal of the time-domain band pass signals is sampled on a regular time-grid that is independent of the carrier signal. The amount of neural stimulation (current, charge) is, as in the low-frequency region, determined by the amplitude of the modulator envelope signal.
The sampling of the band pass signal modulator envelope signals is thus irregular and carrier synchronous in the low-frequency stimulation channels, and regular and carrier asynchronous in the mid- to high-frequency stimulation channels. So the nervous structures of the inner ear receive these two different types of stimulation patterns.
An algorithm for generating an irregular continuous interleaved stimulation pattern is described in Sit et al., A Low-Power Asynchronous Interleaved Sampling Algorithm For Cochlear Implants That Encodes Envelope And Phase Information, IEEE Trans. Biomed. Eng., vol. 54, no. 1, pp. 138-149, January 2007; incorporated herein by reference. The described algorithm includes the following steps:                1) The system receives as inputs half-wave rectified currents from a bank of band pass analysis filters. These could be actual currents such as those generated by an analog processor, or a digital version as produced by a digital signal processor.        2) Each stimulation channel is associated with an integrate-and-fire neuron that receives the current input from that channel to charge up its neuronal capacitance from the ground state. This begins what is referred to as a “race-to-spike.”        3) The first neuron to reach a fixed voltage threshold “wins” and resets all capacitors back to zero. This ensures that the interleaved stimulation requirement is satisfied, since there can be only one winner.        4) The winning neuron then fires a current spike (which is an asynchronous timing event) on its electrode that is scaled by the channel envelope energy.        5) Once a neuron wins, its input current is inhibited (i.e., weakened) for a period determined by a relaxation time constant, to prevent it from winning repeatedly.        6) After the winning neuron has fired its spike, the neuronal “race-to-spike” (Step 2) is started again.        
In U.S. Pat. No. 7,310,558, another electrode stimulation strategy is presented which produces irregular stimulation on all channels. The algorithm describes:                1) Processing a received audio signal to define signals in a set of frequency channels,        2) Determining a time and intensity for each of one or more peaks in each of the frequency signals,        3) Prioritizing each of the peaks according to a predetermined instruction set,        4) Specifying a minimum time interval between the peaks of each of the frequency signals,        5) Discarding peaks occurring within a minimum time interval,        6) Placing non-discarded peaks, in order of priority, into time slots of a buffer corresponding to the times the non-discarded peaks occur in the signals, and        7) Outputting from the buffer a set of data for use in generating stimulus instructions.        